{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from collections import defaultdict\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 长距离序列预测任务"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 单变量时序序列预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_results = '/tmp/JJK/JJK/tpgn-paper-and-codes/TPGN/result.txt'"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(40, 40)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读取txt\n",
    "with open(path_results, 'r') as f:\n",
    "    lines = f.readlines()\n",
    "    lines = [line.strip() for line in lines if len(line.strip())]\n",
    "\n",
    "# 提取数据\n",
    "dict_model_dataset_task2mse_mae = defaultdict(tuple)\n",
    "dict_model_dataset_task2time = defaultdict(tuple)\n",
    "for i in range(0, len(lines), 2):\n",
    "    settings = lines[i].split('_')\n",
    "    ft = settings[5]\n",
    "    if ft != 'ftS':\n",
    "        continue\n",
    "    metrics = lines[i+1].split(', ')\n",
    "    model_dataset_task  = f\"{settings[1]}_{settings[4]}_{settings[6]+'->'+settings[8]}\"\n",
    "    mse = float(metrics[0][4:])\n",
    "    mae = float(metrics[1][4:])\n",
    "    time_train = float(metrics[2].split(':')[1])\n",
    "    time_test = float(metrics[3].split(':')[1])\n",
    "\n",
    "    dict_model_dataset_task2mse_mae[model_dataset_task] = (mse, mae)\n",
    "    dict_model_dataset_task2time[model_dataset_task] = (time_train, time_test)\n",
    "\n",
    "len(dict_model_dataset_task2mse_mae), len(dict_model_dataset_task2time)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(tuple,\n",
       "            {'TPGN_electricity_sl168->pl168': (0.32024189829826355,\n",
       "              0.20259785652160645),\n",
       "             'TPGN_electricity_sl168->pl336': (0.33799606561660767,\n",
       "              0.2200021743774414),\n",
       "             'TPGN_electricity_sl168->pl720': (0.3439892828464508,\n",
       "              0.21977540850639343),\n",
       "             'TPGN_electricity_sl168->pl1440': (0.4019887447357178,\n",
       "              0.2735670804977417),\n",
       "             'TPGN_traffic_sl168->pl168': (0.18491089344024658,\n",
       "              0.11795633286237717),\n",
       "             'TPGN_traffic_sl168->pl336': (0.18887171149253845,\n",
       "              0.11682366579771042),\n",
       "             'TPGN_traffic_sl168->pl720': (0.2065790444612503,\n",
       "              0.12860439717769623),\n",
       "             'TPGN_traffic_sl168->pl1440': (0.21559685468673706,\n",
       "              0.1405131220817566),\n",
       "             'TPGN_ETTh1_sl168->pl168': (0.25188207626342773,\n",
       "              0.10512199252843857),\n",
       "             'TPGN_ETTh1_sl168->pl336': (0.26062822341918945,\n",
       "              0.10989799350500107),\n",
       "             'TPGN_ETTh1_sl168->pl720': (0.2937810719013214,\n",
       "              0.13746017217636108),\n",
       "             'TPGN_ETTh1_sl168->pl1440': (0.2946576774120331,\n",
       "              0.1345820128917694),\n",
       "             'TPGN_ETTh2_sl168->pl168': (0.35738977789878845,\n",
       "              0.21058706939220428),\n",
       "             'TPGN_ETTh2_sl168->pl336': (0.37239789962768555,\n",
       "              0.21886146068572998),\n",
       "             'TPGN_ETTh2_sl168->pl720': (0.3887802064418793,\n",
       "              0.23634089529514313),\n",
       "             'TPGN_ETTh2_sl168->pl1440': (0.4085550904273987,\n",
       "              0.2524023950099945),\n",
       "             'TPGN_Weather_sl168->pl168': (0.05717436969280243,\n",
       "              0.005082092247903347),\n",
       "             'TPGN_Weather_sl168->pl336': (0.06690049171447754,\n",
       "              0.007345061283558607),\n",
       "             'TPGN_Weather_sl168->pl720': (0.07163765281438828,\n",
       "              0.008439437486231327),\n",
       "             'TPGN_Weather_sl168->pl1440': (0.07118412107229233,\n",
       "              0.008123170584440231),\n",
       "             'WITRAN_electricity_sl168->pl168': (0.3512403070926666,\n",
       "              0.23253899812698364),\n",
       "             'WITRAN_electricity_sl168->pl336': (0.37501588463783264,\n",
       "              0.2600885331630707),\n",
       "             'WITRAN_electricity_sl168->pl720': (0.40605199337005615,\n",
       "              0.30067896842956543),\n",
       "             'WITRAN_electricity_sl168->pl1440': (0.39100977778434753,\n",
       "              0.2710622251033783),\n",
       "             'WITRAN_traffic_sl168->pl168': (0.24879363179206848,\n",
       "              0.1730237454175949),\n",
       "             'WITRAN_traffic_sl168->pl336': (0.2718483805656433,\n",
       "              0.19163967669010162),\n",
       "             'WITRAN_traffic_sl168->pl720': (0.27718308568000793,\n",
       "              0.195897176861763),\n",
       "             'WITRAN_traffic_sl168->pl1440': (0.3005868196487427,\n",
       "              0.22563983500003815),\n",
       "             'WITRAN_ETTh1_sl168->pl168': (0.30241236090660095,\n",
       "              0.14024989306926727),\n",
       "             'WITRAN_ETTh1_sl168->pl336': (0.362122505903244,\n",
       "              0.1942078024148941),\n",
       "             'WITRAN_ETTh1_sl168->pl720': (0.5461316108703613,\n",
       "              0.4010356664657593),\n",
       "             'WITRAN_ETTh1_sl168->pl1440': (0.3195866048336029,\n",
       "              0.15872599184513092),\n",
       "             'WITRAN_ETTh2_sl168->pl168': (0.3925044536590576,\n",
       "              0.25434279441833496),\n",
       "             'WITRAN_ETTh2_sl168->pl336': (0.39423492550849915,\n",
       "              0.24751874804496765),\n",
       "             'WITRAN_ETTh2_sl168->pl720': (0.39694318175315857,\n",
       "              0.2466678023338318),\n",
       "             'WITRAN_ETTh2_sl168->pl1440': (0.4192884564399719,\n",
       "              0.2745357155799866),\n",
       "             'WITRAN_Weather_sl168->pl168': (0.05937381088733673,\n",
       "              0.005401018541306257),\n",
       "             'WITRAN_Weather_sl168->pl336': (0.056913796812295914,\n",
       "              0.005339364055544138),\n",
       "             'WITRAN_Weather_sl168->pl720': (0.051270682364702225,\n",
       "              0.004025655332952738),\n",
       "             'WITRAN_Weather_sl168->pl1440': (0.07231063395738602,\n",
       "              0.008377996273338795)})"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dict_model_dataset_task2mse_mae"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                       MSE       MAE\n",
      "TPGN_electricity_sl168->pl168     0.320242  0.202598\n",
      "TPGN_electricity_sl168->pl336     0.337996  0.220002\n",
      "TPGN_electricity_sl168->pl720     0.343989  0.219775\n",
      "TPGN_electricity_sl168->pl1440    0.401989  0.273567\n",
      "TPGN_traffic_sl168->pl168         0.184911  0.117956\n",
      "TPGN_traffic_sl168->pl336         0.188872  0.116824\n",
      "TPGN_traffic_sl168->pl720         0.206579  0.128604\n",
      "TPGN_traffic_sl168->pl1440        0.215597  0.140513\n",
      "TPGN_ETTh1_sl168->pl168           0.251882  0.105122\n",
      "TPGN_ETTh1_sl168->pl336           0.260628  0.109898\n",
      "TPGN_ETTh1_sl168->pl720           0.293781  0.137460\n",
      "TPGN_ETTh1_sl168->pl1440          0.294658  0.134582\n",
      "TPGN_ETTh2_sl168->pl168           0.357390  0.210587\n",
      "TPGN_ETTh2_sl168->pl336           0.372398  0.218861\n",
      "TPGN_ETTh2_sl168->pl720           0.388780  0.236341\n",
      "TPGN_ETTh2_sl168->pl1440          0.408555  0.252402\n",
      "TPGN_Weather_sl168->pl168         0.057174  0.005082\n",
      "TPGN_Weather_sl168->pl336         0.066900  0.007345\n",
      "TPGN_Weather_sl168->pl720         0.071638  0.008439\n",
      "TPGN_Weather_sl168->pl1440        0.071184  0.008123\n",
      "WITRAN_electricity_sl168->pl168   0.351240  0.232539\n",
      "WITRAN_electricity_sl168->pl336   0.375016  0.260089\n",
      "WITRAN_electricity_sl168->pl720   0.406052  0.300679\n",
      "WITRAN_electricity_sl168->pl1440  0.391010  0.271062\n",
      "WITRAN_traffic_sl168->pl168       0.248794  0.173024\n",
      "WITRAN_traffic_sl168->pl336       0.271848  0.191640\n",
      "WITRAN_traffic_sl168->pl720       0.277183  0.195897\n",
      "WITRAN_traffic_sl168->pl1440      0.300587  0.225640\n",
      "WITRAN_ETTh1_sl168->pl168         0.302412  0.140250\n",
      "WITRAN_ETTh1_sl168->pl336         0.362123  0.194208\n",
      "WITRAN_ETTh1_sl168->pl720         0.546132  0.401036\n",
      "WITRAN_ETTh1_sl168->pl1440        0.319587  0.158726\n",
      "WITRAN_ETTh2_sl168->pl168         0.392504  0.254343\n",
      "WITRAN_ETTh2_sl168->pl336         0.394235  0.247519\n",
      "WITRAN_ETTh2_sl168->pl720         0.396943  0.246668\n",
      "WITRAN_ETTh2_sl168->pl1440        0.419288  0.274536\n",
      "WITRAN_Weather_sl168->pl168       0.059374  0.005401\n",
      "WITRAN_Weather_sl168->pl336       0.056914  0.005339\n",
      "WITRAN_Weather_sl168->pl720       0.051271  0.004026\n",
      "WITRAN_Weather_sl168->pl1440      0.072311  0.008378\n"
     ]
    }
   ],
   "source": [
    "# 将数据转换为DataFrame\n",
    "df = pd.DataFrame(dict_model_dataset_task2mse_mae)\n",
    "df.index = ['MSE', 'MAE']\n",
    "df = df.T\n",
    "print(df)\n",
    "\n",
    "# 输出 csv 文件\n",
    "dir = \"./files_csv_for_results/\"\n",
    "df.to_csv(dir+'long-range-forecasting-task_with_ftS.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 多变量时序序列预测（多对一）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(15, 15)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读取txt\n",
    "with open(path_results, 'r') as f:\n",
    "    lines = f.readlines()\n",
    "    lines = [line.strip() for line in lines if len(line.strip())]\n",
    "\n",
    "dict_model_dataset_task2mse_mae = defaultdict(tuple)\n",
    "dict_model_dataset_task2time = defaultdict(tuple)\n",
    "for i in range(0, len(lines), 2):\n",
    "    settings = lines[i].split('_')\n",
    "    ft = settings[5]\n",
    "    if ft != 'ftMS':\n",
    "        continue\n",
    "    metrics = lines[i+1].split(', ')\n",
    "    model_dataset_task  = f\"{settings[1]}_{settings[4]}_{settings[6]+'->'+settings[8]}\"\n",
    "    mse = float(metrics[0][4:])\n",
    "    mae = float(metrics[1][4:])\n",
    "    time_train = float(metrics[2].split(':')[1])\n",
    "    time_test = float(metrics[3].split(':')[1])\n",
    "\n",
    "    dict_model_dataset_task2mse_mae[model_dataset_task] = (mse, mae)\n",
    "    dict_model_dataset_task2time[model_dataset_task] = (time_train, time_test)\n",
    "\n",
    "len(dict_model_dataset_task2mse_mae), len(dict_model_dataset_task2time)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                     MSE       MAE\n",
      "TPGN_electricity_sl168->pl168   0.493913  0.419207\n",
      "TPGN_electricity_sl168->pl336   0.504087  0.448283\n",
      "TPGN_electricity_sl168->pl720   0.487640  0.412549\n",
      "TPGN_electricity_sl168->pl1440  0.492326  0.411472\n",
      "TPGN_ETTh1_sl168->pl168         1.087632  1.704566\n",
      "TPGN_ETTh1_sl168->pl336         1.039025  1.557356\n",
      "TPGN_ETTh1_sl168->pl720         0.994604  1.444946\n",
      "TPGN_ETTh1_sl168->pl1440        0.975300  1.410718\n",
      "TPGN_ETTh2_sl168->pl336         0.428564  0.290724\n",
      "TPGN_ETTh2_sl168->pl720         0.420651  0.273267\n",
      "TPGN_ETTh2_sl168->pl1440        0.439484  0.292372\n",
      "TPGN_Weather_sl168->pl168       0.081261  0.011200\n",
      "TPGN_Weather_sl168->pl336       0.094700  0.015850\n",
      "TPGN_Weather_sl168->pl720       0.092700  0.014559\n",
      "TPGN_Weather_sl168->pl1440      0.084561  0.011741\n"
     ]
    }
   ],
   "source": [
    "# 将数据转换为DataFrame\n",
    "df = pd.DataFrame(dict_model_dataset_task2mse_mae)\n",
    "df.index = ['MSE', 'MAE']\n",
    "df = df.T\n",
    "print(df)\n",
    "\n",
    "# 输出 csv 文件\n",
    "dir = \"./files_csv_for_results/\"\n",
    "df.to_csv(dir+'long-range-forecasting-task_with_ftMS.csv')"
   ]
  }
 ],
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